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Paper defect detection method based on bit planes

A technology of paper defect detection and bit plane, applied in the field of paper defect detection, can solve the problems of complex fuzzy logic algorithm recognition and subsequent processing, great influence on detection results, one-dimensional autoregressive algorithm cannot be used for texture modeling and defect detection, etc. , to achieve the effect of simple and easy implementation, large market potential, and simple and easy implementation

Inactive Publication Date: 2016-02-03
SHAANXI UNIV OF SCI & TECH
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Problems solved by technology

The one-dimensional autoregressive algorithm cannot be used for texture modeling and defect detection. The fuzzy logic algorithm is more complicated for the identification and subsequent processing of defects. The selection of the confidence level of the paper defect detection method based on co-occurrence matrix and self-organizing neural network has a great influence on the detection results. great influence

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  • Paper defect detection method based on bit planes
  • Paper defect detection method based on bit planes
  • Paper defect detection method based on bit planes

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Embodiment Construction

[0029] Below in conjunction with accompanying drawing, the present invention is described in further detail:

[0030] In the present invention, the image containing paper defects is used as the detected object, and the processing flow is as follows: figure 1 As shown, the specific implementation steps are as follows:

[0031] Step1. Obtain the original image of the tested paper through the CCD camera and convert it into a grayscale image.

[0032] Step2. Perform adaptive median filter processing on the obtained grayscale image to eliminate noise in the image. It can adaptively adjust the size of the filter window and output the filter result according to the degree of interference of the image by noise. The initial filter radius is selected as 3. The maximum filter radius is 10. The specific method is to use the filter window to perform sliding scanning from the upper left corner of the original image to judge whether there are noise points. The basis for judging is whether ...

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Abstract

The invention discloses a paper defect detection method based on bit planes. The paper defect detection method comprises the following steps of firstly, obtaining an original image of the tested paper, and converting into a grayscale image; pretreating the grayscale image, so as to eliminate the noise in the image; decomposing the bit plane of the pretreated grayscale image to obtain eight bit planes of the image; using Gray code to enhance the bit planes, so as to obtain eight enhanced bit planes of the grayscale image; finally, selecting the sixth enhanced bit plane, and segmenting the image, so as to obtain the final detection result. The paper defect detection method has the advantages that while the rapidity of algorithm is guaranteed, the defect can be well detected; the anti-interference property and positioning accuracy are better, and the operation is simple.

Description

technical field [0001] The invention relates to a paper defect detection method, in particular to a bit plane-based paper defect detection method. Background technique [0002] As paper machine speeds continue to increase, paper runs the risk of developing more defects. Since manual identification of paper appearance defects requires a large amount of manpower, and the recognition rate is low and work efficiency is low, it is no longer possible to detect paper appearance defects with the naked eye. It has become an irreplaceable trend to use machine vision to detect the appearance of paper defects. [0003] At present, the methods of using machine vision to detect the appearance of paper defects are generally divided into three categories: threshold method, morphological method, and gray level statistical method. Among them, the threshold method sets different thresholds according to different paper defects, which is a simple and effective image segmentation method, but th...

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Application Information

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IPC IPC(8): G01N21/88G06T7/00
Inventor 亢洁潘思璐王晓东
Owner SHAANXI UNIV OF SCI & TECH
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